Introduction
Wheat (Triticum aestivum L.), the world's second most consumed cereal, is crucial in maintaining global food security. The growing demand is projected to reach as high as 2050, which has made it imperative to improve performance characteristics in conditions of limited water availability. In Iran, a tremendous amount of wheat cultivation is usually carried out through dryland agriculture. The strategy of selecting stress-resistant varieties with high yields thus stands out as an imperative approach towards successful cultivation. Drought-resistant varieties with high yields are favored as an important approach towards successful cultivation. Genetic diversity in agronomical traits such as flowering days, kernel weight, plant height, and spike characteristics forms the basis for the creation of stress-resistant varieties. The use of statistical approaches in the analysis of the germplasm helps to identify and introduce better genotypes alongside the selection of better parents and the production of better recombinants. For this research work, 169 bread wheat genotypes were chosen including three control checks: Karim, Qaboos, and Aftab, and were studied using an augmented design approach in tropical dryland agriculture. The primary objective of this research work is to identify high-yielding genotypes with sound agronomical traits.
Materials and Methods
The study was carried out during the 2019–2020 harvest period at the Gachsaran Agricultural Research and Education Center (National Dryland Research Station) employing an augmented design with randomized complete block checks. Each plot consisted of six rows of 6 m length. Morphological and phenological traits, including days to heading, days to physiological maturity, plant height (cm), spike length (cm), thousand-grain weight (g), and grain yield (kg ha-1), were recorded. Analysis of variance was performed for the check cultivars, and adjusted means for all genotypes were estimated using the augmented design model. Cluster analysis was conducted using Euclidean distance and Ward’s method in R, Pearson’s correlation coefficients were calculated among traits, and principal component analysis was applied. Finally, a multi-trait stability index (MTSI), weighted according to the importance of traits under dryland conditions, was computed in Python to identify superior genotypes.
Results and Discussion
Notable disparities were observed among the check cultivars for plant height and thousand-grain weight. The coefficient of variation for grain yield was the highest, indicating considerable genetic diversity affecting this characteristic. Yield varied from 3202 kg per hectare (G119) to 7502 kg per hectare (G103), with an overall average of 5375 kg per hectare. Genotype classification by cluster analysis identified three distinct groups, with the second cluster yielding the highest mean output. A positive and significant correlation was found between grain yield and plant height and spike length, whereas a negative correlation existed with days to maturity and thousand-grain weight. Principal component analysis showed that the first two principal components accounted for 51.12% of the total variation; specifically, PC1 was associated with phenological traits (Days to heading, Days to maturity) and PC2 was linked to yield-related traits (Thousand grain weight, Spike length, yield). No single genotype outperformed all traits, underlining the need for multi-trait selection. According to the weighted MTSI, genotypes G80, G110, G102, G103, G79, G160, G130, G101, G81, and G107 were identified as superior, exhibiting a combination of high yield, long spikes, desirable grain weight, and early maturity.
Conclusion
The study found high genetic variation among different strains of bread wheat when grown in dryland conditions. However, no genotypes showed superior performance across all characteristics due to a negative correlation between phenological and yield characteristics existed. The above factors prove the importance of genotype selection based on multiple weighted characters. The examined strains have a high potential to be used as new strains that can withstand drought conditions and ensure higher yield. This will improve the stability and yield of wheat in low rainfall and dryland conditions.